Karin Gaensler

2.5k total citations
42 papers, 1.4k citations indexed

About

Karin Gaensler is a scholar working on Molecular Biology, Genetics and Hematology. According to data from OpenAlex, Karin Gaensler has authored 42 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 12 papers in Genetics and 11 papers in Hematology. Recurrent topics in Karin Gaensler's work include Virus-based gene therapy research (10 papers), RNA Interference and Gene Delivery (8 papers) and Acute Myeloid Leukemia Research (7 papers). Karin Gaensler is often cited by papers focused on Virus-based gene therapy research (10 papers), RNA Interference and Gene Delivery (8 papers) and Acute Myeloid Leukemia Research (7 papers). Karin Gaensler collaborates with scholars based in United States, United Kingdom and Australia. Karin Gaensler's co-authors include Gerald S. Lipshutz, Robert J. Debs, Denny Liggitt, Yong Liu, Wendy Zhong, Christopher H. Contag, Yimin Shi, Yuan Cao, Jonathan Hardy and Bryce A. Kerlin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nano Letters.

In The Last Decade

Karin Gaensler

42 papers receiving 1.3k citations

Peers

Karin Gaensler
Giulia Pavani United States
C. Anthony Blau United States
So C. Wong United States
Hojun Li United States
J. Düllmann Germany
Belinda K. Singleton United Kingdom
J. G. J. Bauman Netherlands
Kathrin M. Bernt United States
Julia Hauer Germany
Zhi Hong Lu United States
Giulia Pavani United States
Karin Gaensler
Citations per year, relative to Karin Gaensler Karin Gaensler (= 1×) peers Giulia Pavani

Countries citing papers authored by Karin Gaensler

Since Specialization
Citations

This map shows the geographic impact of Karin Gaensler's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Karin Gaensler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karin Gaensler more than expected).

Fields of papers citing papers by Karin Gaensler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karin Gaensler. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Karin Gaensler. The network helps show where Karin Gaensler may publish in the future.

Co-authorship network of co-authors of Karin Gaensler

This figure shows the co-authorship network connecting the top 25 collaborators of Karin Gaensler. A scholar is included among the top collaborators of Karin Gaensler based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Karin Gaensler. Karin Gaensler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Huang, Li‐Wen, Ying Shi, Charalambos Andreadis, et al.. (2023). Association of geriatric measures and global frailty with cognitive decline after allogeneic hematopoietic cell transplantation in older adults. Journal of Geriatric Oncology. 14(8). 101623–101623. 5 indexed citations
2.
Huang, Li‐Wen, Ying Sheng, Charalambos Andreadis, et al.. (2022). Patterns and Predictors of Functional Decline after Allogeneic Hematopoietic Cell Transplantation in Older Adults. Transplantation and Cellular Therapy. 28(6). 309.e1–309.e9. 3 indexed citations
3.
Mannis, Gabriel N., Thomas Martin, Lloyd E. Damon, et al.. (2016). Quantification of Acute Lymphoblastic Leukemia Clonotypes in Leukapheresed Peripheral Blood Progenitor Cells Predicts Relapse Risk after Autologous Hematopoietic Stem Cell Transplantation. Biology of Blood and Marrow Transplantation. 22(6). 1030–1036. 9 indexed citations
4.
5.
Mannis, Gabriel N., Thomas G. Martin, Lloyd E. Damon, et al.. (2015). Long-term outcomes of patients with intermediate-risk acute myeloid leukemia treated with autologous hematopoietic cell transplant in first complete remission. Leukemia & lymphoma. 57(7). 1560–1566. 8 indexed citations
6.
Mannis, Gabriel N., Charalambos Andreadis, Aaron C. Logan, et al.. (2015). A Phase I Study of Targeted, Dose-Escalated Intravenous Busulfan in Combination With Etoposide as Myeloablative Therapy for Autologous Stem Cell Transplantation in Acute Myeloid Leukemia. Clinical Lymphoma Myeloma & Leukemia. 15(6). 377–383. 2 indexed citations
7.
Tye, Gee Jun, Kyriaki Ioannou, Eunice Amofah, et al.. (2015). The combined molecular adjuvant CASAC enhances the CD8+ T cell response to a tumor-associated self-antigen in aged, immunosenescent mice. Immunity & Ageing. 12(1). 6–6. 9 indexed citations
8.
Park, Ilwoo, Joydeep Mukherjee, Motokazu Ito, et al.. (2014). Changes in Pyruvate Metabolism Detected by Magnetic Resonance Imaging Are Linked to DNA Damage and Serve as a Sensor of Temozolomide Response in Glioblastoma Cells. Cancer Research. 74(23). 7115–7124. 58 indexed citations
9.
Keller, Jesse W., Charalambos Andreadis, Lloyd E. Damon, et al.. (2014). Hematopoietic cell transplantation comorbidity index (HCT-CI) is predictive of adverse events and overall survival in older allogeneic transplant recipients. Journal of Geriatric Oncology. 5(3). 238–244. 10 indexed citations
10.
Shi, Yimin, et al.. (2013). Role of antigen-specific regulatory CD4+CD25+ T cells in tolerance induction after neonatal IP administration of AAV-hF.IX. Gene Therapy. 20(10). 987–996. 10 indexed citations
11.
Falahati, Rustom, et al.. (2012). Chemoselection of Allogeneic HSC After Murine Neonatal Transplantation Without Myeloablation or Post-transplant Immunosuppression. Molecular Therapy. 20(11). 2180–2189. 9 indexed citations
12.
Mintz, Paul J., Pål Sætrom, Vikash Reebye, et al.. (2012). MicroRNA-181a* Targets Nanog in a Subpopulation of CD34+ Cells Isolated From Peripheral Blood. Molecular Therapy — Nucleic Acids. 1. e34–e34. 13 indexed citations
13.
Alhashem, Yousef N., et al.. (2011). Transcription Factors KLF1 and KLF2 Positively Regulate Embryonic and Fetal β-Globin Genes through Direct Promoter Binding. Journal of Biological Chemistry. 286(28). 24819–24827. 37 indexed citations
14.
15.
Keys, Janelle R., Michael R. Tallack, Ye Zhan, et al.. (2008). A mechanism for Ikaros regulation of human globin gene switching. British Journal of Haematology. 141(3). 398–406. 35 indexed citations
16.
Lipshutz, Gerald S., et al.. (2001). In Utero Delivery of Adeno-Associated Viral Vectors: Intraperitoneal Gene Transfer Produces Long-Term Expression. Molecular Therapy. 3(3). 284–292. 134 indexed citations
17.
Lipshutz, Gerald S., et al.. (2000). Reexpression Following Readministration of an Adenoviral Vector in Adult Mice after Initial in Utero Adenoviral Administration. Molecular Therapy. 2(4). 374–380. 48 indexed citations
18.
Gaensler, Karin, Steven W. Bruch, Denny Liggitt, et al.. (1999). Fetal gene transfer by transuterine injection of cationic liposome–DNA complexes. Nature Biotechnology. 17(12). 1188–1192. 26 indexed citations
19.
Liu, Yong, et al.. (1995). Cationic Liposome-mediated Intravenous Gene Delivery. Journal of Biological Chemistry. 270(42). 24864–24870. 195 indexed citations
20.
Debs, Robert J., et al.. (1992). Prolonged Transgene Expression in Rodent Lung Cells. American Journal of Respiratory Cell and Molecular Biology. 7(4). 406–413. 23 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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